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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Scaling Multiagent Systems with Process Rewards · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2601.23228/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2601.23228/feed.xml" rel="self" type="application/rss+xml" /><item><title>Scaling Multiagent Systems with Process Rewards — HN submission</title><link>https://news.ycombinator.com/item?id=46889889</link><guid isPermaLink="false">urn:hackerpapers:submission:2601.23228:46889889</guid><pubDate>Wed, 04 Feb 2026 18:45:55 GMT</pubDate><description>&lt;p&gt;Mappa – Fine-tune ANY multi-agent LLM systems end-to-end with AI coaches&lt;/p&gt;&lt;p&gt;Blog: https://ltjed.github.io/MAPPA/ Paper: https://arxiv.org/abs/2601.23228 Code: https://github.com/ltjed/multiagent-coaching Twitter: https://x.com/t_ed_li/status/2019114121250370021&lt;/p&gt;&lt;p&gt;3 points; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2601.23228/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
